Metabolomics-Based Elucidation of the Lipid-Lowering Mechanisms of Monascus Vinegar Polysaccharides

TL;DR

This study explores how Monascus vinegar polysaccharides lower lipids in mice by affecting specific metabolic pathways.

Contribution

The study identifies specific metabolic pathways modulated by Monascus vinegar polysaccharides in lipid and antioxidant regulation.

Findings

MVP significantly reduced serum and liver lipid levels in hyperlipidemia mice.

MVP improved liver histopathology and increased antioxidant enzyme activity.

Key metabolic pathways affected include arachidonic acid and glutathione metabolism.

Abstract

Monascus vinegar (MV) is a functional food containing various bioactive components, which has attracted significant research attention due to the unique health benefits conferred by these active functional ingredients. This study aimed to investigate the mechanism by which Monascus vinegar polysaccharides (MVPs) prevent hyperlipidemia. We established a hyperlipidemia mouse model using a high-fat diet (HFD) and conducted an 8-week intervention experiment. Results showed that MVP significantly reduced serum and liver lipid levels in mice, increased the activity of liver antioxidant enzymes, and downregulated the expression of serum proinflammatory cytokines. Hematoxylin and eosin (H&E) staining revealed that MVP significantly improved liver histopathological abnormalities. Enrichment analysis of key differential metabolites identified four potential metabolic pathways and mapped them to the MVP and model groups. The analysis revealed the involvement of pathways related to arachidonic acid metabolism, glutathione metabolism, alanine–aspartate–glutamate metabolism, and pyrimidine metabolism. After MVP intervention, key metabolites within these pathways were significantly improved. MVP may influence lipid metabolism through modulation of these pathways. This study provides theoretical support for the application and development of MVP in the functional food sector.

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Full text

1. Introduction

Hyperlipidaemia is a chronic condition with significant potential to adversely impact health [1]. With the global rise in sedentary lifestyles, obesity, and unhealthy dietary patterns, dyslipidemia has emerged as a leading modifiable risk factor for atherosclerotic cardiovascular disease [2,3]. Beyond host genetics and diet, the intricate relationship between gut microbiota (GM) and host lipid metabolism has been recognized as a crucial component in the mechanisms underlying dyslipidemia and its therapeutic strategies [4]. Currently, drug therapy remains an effective approach for treating hyperlipidemia, with statins being the most widely used class of medications. However, the adverse side effects of medication may reduce patient compliance, thereby affecting the efficacy of the medication. In contrast, dietary interventions are associated with a lower incidence of adverse effects and superior safety profiles [5,6]. Earlier research has shown that bioactive compounds, such as tea polyphenols, resveratrol, and quercetin, effectively reduce blood lipid levels by inhibiting cholesterol absorption and enhancing bile acid excretion [7,8,9]. Additionally, polysaccharides from Caulerpa lentillifera (CLP) have been shown to effectively alleviate HFD-induced hyperlipidaemia, potentially through modulation of the gut microbiota–bile acid pathway [10]. Recently, the incorporation of food-derived bioactive components into daily diets has gained recognition as a viable nutritional strategy for the effective management of hyperlipidaemia [11,12].

Monascus vinegar (MV) is a fermented liquid condiment produced through the aging of rice with Monascus purpureus serving as the saccharifying agent, a feature that distinguishes it from many cereal vinegars that rely on conventional starters and solid-state processes. The fermentation process driven by Monascus purpureus forms a complex matrix rich in organic acids, polysaccharides, and various bioactive components. Polysaccharides are one of the key lipid-lowering components in MV, with effects including anti-dyslipidemia, antioxidant activity, anti-inflammatory properties, blood pressure regulation, and modulation of intestinal function [13]. Mechanistically, polysaccharides resist complete digestion and absorption in the small intestine and reach the colon, where they serve as fermentable substrates for gut microbes. This can selectively enrich specific taxa and reshape community function, altering the production of key metabolites such as short-chain fatty acids. These shifts may in turn modulate intestinal barrier integrity, inflammatory tone and energy-sensing pathways, providing a plausible route by which polysaccharides improve lipid metabolism. Recent studies have shown that polysaccharides perform a range of crucial physiological functions, such as enhancing macrophage phagocytic activity, promoting spleen lymphocyte proliferation, increasing immune organ indices, and mitigating immunosuppression [14]. Polysaccharides derived from green radish can improve blood lipid disorders and liver injury in high-fat diet-fed mice by increasing SCFA production and modulating gut microbiota [15]. Similarly, polysaccharides from Sargassum fusiforme have been reported to simultaneously regulate gut microbiota and metabolite profiles, thereby alleviating high-fat diet-induced hyperlipidemia phenotypes [16]. Additionally, polysaccharides have been shown to improve hyperlipidemia by regulating lipid metabolism-associated genes in hepatic tissue and inhibiting the NF-κB inflammatory pathway [17]. Previous studies have demonstrated that Gougunao tea polysaccharide (GTP40) activates the AMPK signaling pathway, upregulating lipolysis genes and downregulating lipogenesis genes to alleviate lipid metabolism disorders and oxidative stress in mice on a high-fat diet [18]. MV may help prevent or mitigate hyperlipidaemia by modulating the gut microbiota and, through the actions of key bioactive components and their synergistic interactions, improving lipid metabolic dysfunction and chronic inflammation associated with metabolic disease [19]. However, the mechanisms responsible for the lipid-lowering effects of specific polysaccharide fractions in MV remain unclear; in particular, their regulation of intestinal metabolism at the metabolomic level remains insufficiently studied. Therefore, this work seeks to clarify the potential lipid-lowering mechanisms of Monascus vinegar polysaccharides (MVP). Specifically, we integrate molecular biology approaches with untargeted metabolomics to systematically examine how MVP modulates pathways involved in dysregulated lipid metabolism.

In this study, using MVP as the study focus, we established a high-fat diet (HFD) mouse model. The hypolipidaemic effects were evaluated by quantifying serum and hepatic biochemical indices and antioxidant status, together with liver histopathology, intestinal barrier function assessment and mouse gut untargeted metabolomics. The aim is to elucidate the mechanism of action of MVP as an effective bioactive substance for the treatment of hyperlipidemia.

2. Materials and Methods

2.1. Materials and Reagents

Shandong Yutu Food Co., Ltd. (Zibo, China) provided Monascus vinegar stock solution. Feed was purchased from Tianjin Aoyide Experimental Supplies Co., Ltd. (Tianjin, China). The standard chow contained 59% carbohydrate, 21.1% protein, 4.2% fat, 4.9% fiber, and 8% ash, with minerals including 1.0% phosphorus and 1.8% calcium. The high-fat diet (HFD) was prepared by fortifying the standard chow with cholesterol (2%), lard (10%), porcine bile salts (0.2%), egg yolk powder (10%), and sugar (5%). Total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL-C), high-density lipoprotein (HDL-C), malondialdehyde (MDA), superoxide dismutase (SOD), interleukin-2 (IL-2), interleukin-6 (IL-6), interleukin-8 (IL-8), tumor necrosis factor-α (TNF-α), diacylglycerol O-acyltransferase (DGAT), lipoprotein lipase (LPL), hepatic lipase (HL), carnitine palmitoyltransferase 1 (CPT-1), and glutathione (GSH) and acetyl-CoA carboxylase (ACC) kits were all purchased from Shanghai Enzyme-linked Biotechnology Co., Ltd. (Shanghai, China). Hematoxylin and eosin (H&E) staining solution was purchased from Beijing Solarbio Technology Co., Ltd. (Beijing, China); chromatographic-grade isopropanol was purchased from Burdick & Jackson Co., Ltd. (Beijing, China); chromatographic-grade acetonitrile and formic acid were both purchased from Shanghai Sigma-Aldrich Trading Co., Ltd. (Shanghai, China).

2.2. Preparation of Monascus Vinegar Polysaccharide

We centrifuged the crude MVP extract at 8000 rpm for 10 min and retained the supernatant, then rotary-evaporated it at 80 °C to reduce the volume to ~20–33% of the original. We added four volumes of anhydrous ethanol, incubated it at 4 °C overnight to precipitate, and then centrifuged it (8000 rpm, 10 min). We resuspended the pellet in water to 1/5 of the original volume. We removed proteins by repeatedly extracting with Sevage reagent (chloroform:n-butanol, v/v = 4:1) at a Sevage reagent:polysaccharide ratio of 1:4. We removed residual organic solvent by rotary evaporation at 60 °C. We dialyzed the aqueous phase against running water for 24 h using a 3500 Da dialysis bag. We collected the dialysate and freeze-dried it for storage.

2.3. Nontargeted Metabolomics Analysis

We accurately weighed 100 mg of each cecal content sample into a 2 mL centrifuge tube and added 1.0 mL of saline and 10 μL of 0.3 mg/mL L-2-chlorophenylalanine (for signal correction). This was using a cryogenic grinding instrument, then 3.0 mL of acetonitrile was added and vortexed thoroughly. We allowed the mixture to stand at 4 °C for 20 min, followed by centrifugation at 14,000 rpm for 15 min (4 °C). The supernatant was collected, dried under a gentle nitrogen stream, and the residue was reconstituted with 100 μL of acetonitrile. This was sonicated (360 W power, 40 kHz frequency) for 20 min, then centrifuged again at 14,000 rpm for 10 min at 4 °C. We performed chromatographic separation on a Dionex UltiMate 3000 UHPLC system (Thermo Fisher Scientific, Waltham, MA, USA) equipped with a Hypersil Gold C18 column (150 mm × 2.1 mm, 1.9 μm; Thermo Fisher Scientific, Waltham, MA, USA). A binary gradient of acetonitrile (A) and 0.1% formic acid in water (B) was used: 0–0.5 min, 5% A; 0.5–15 min, 5–95% A (linear); 15–17 min, 95% A. The flow was 0.3 mL/min, the column temperature was 40 °C, and the injection volume was 2 μL. MS detection employed ESI with the nebulizer at 300 °C and transfer tube at 350 °C; sheath/auxiliary gases were 35/15 arb and spray voltage was 3.5 kV. Full-scan data were collected in positive mode (m/z 100–1500) at 70,000 resolution (FWHM) [20].

2.4. Bioinformatics Analysis

Raw data were acquired using Xcalibur 4.2 and processed in Compound Discoverer 2.1 for peak detection, retention-time alignment, peak grouping/deconvolution and signal normalization to generate a feature table (m/z–RT pairs and peak areas). Features were filtered to improve data quality by removing those with excessive missing values across samples and those with poor reproducibility in QC injections, followed by imputation of remaining missing values and log transformation where appropriate. The processed data matrix was imported into SIMCA for multivariate analysis. PCA was applied to visualize global clustering and flag potential outliers. Group separation was further explored using OPLS-DA, with model validity assessed by cross-validation and 200-permutation tests to check for overfitting. Significant metabolites were defined by VIP > 1 (OPLS-DA) together with p < 0.05 in univariate tests. Pathway enrichment was performed in MetaboAnalyst 4.0, and pathways with p < 0.05 were considered significantly enriched. The KEGG Mapper visualization tool for differential metabolites was employed to map the enriched pathways.

2.5. Animal Experiment Design

Male Kunming mice (3–4 weeks of age; 20 ± 2 g) were maintained under standard husbandry conditions and acclimated on a chow diet with ad libitum access to water. Following acclimation, animals were randomized by a random-number table into four groups (n = 5 per group). There was no statistically significant difference in initial body weight and baseline blood lipid indices among the groups. The vehicle group received a standard diet and daily gavage of distilled water, whereas the model group was fed a high-fat diet (HFD) and administered distilled water by gavage. Two intervention groups were fed the HFD and treated with MVP at 50 mg/kg/d (MVP-L) or 100 mg/kg/d (MVP-H). The doses of MVP (50 mg/kg/d and 100 mg/kg/d) used in this study were based on previous studies evaluating the effects of MVP on lipid metabolism in animal models. Oral gavage was conducted once daily at a consistent time each afternoon, with a fixed dosing volume of 0.2 mL per mouse, for 8 consecutive weeks. At study completion, fresh serum samples were collected using ice-cooled tubes and immediately stored at −80 °C for subsequent analysis. Additionally, liver, small intestine, and colon tissues were collected for further examination. Cecal content samples were flash-frozen in liquid nitrogen and stored at −80 °C. Liver tissues were harvested for biochemical quantification of TG and TC, and for histopathological assessment to evaluate lipid accumulation and structural alterations. Model induction was considered successful when the HFD-fed model group exhibited pronounced hepatic steatosis on histological examination. All experimental procedures were reviewed and approved by the Institutional Animal Health Committee of Tianjin University of Science and Technology (TUST20180522) [21].

2.6. Biochemical Parameters

Serum samples stored at −80 °C were thawed at 4 °C, and the levels of TC, TG, LDL-C, HDL-C, IL-2, IL-6, IL-8, TNF-α, MDA, and SOD activity in the serum were determined according to the kit instructions. Then, 0.1 g of mouse liver was accurately weighed, added to 0.9 mL of pre-cooled physiological saline, and placed in a grinding bead. The liver was ground four times for 30 s each time using a high-speed, low-temperature tissue homogenizer at 4 °C and 60 Hz. After centrifugation of the homogenate (4 °C, 9000 rpm, 10 min), the supernatant was collected. TC, TG, LDL-C, HDL-C, and the activities of ACC, DGAT, LPL, HL, CPT-1, and GSH were measured using commercial assay kits according to the manufacturers’ protocols. Each assay was performed in triplicate.

2.7. H&E and AB-PAS Staining of Mouse Liver and Intestinal Tissues

After euthanasia, approximately 0.1 g of liver, small intestine, and colon tissues were collected and fixed in 10% neutral buffered formalin (pH 7.0) for at least 24 h. Samples were washed with PBS, dehydrated in graded ethanol, cleared with xylene, and paraffin-embedded. Sections were stained with haematoxylin and eosin (H&E) or Alcian blue–periodic acid–Schiff (AB–PAS). Images were examined under a light microscope at 400× magnification.

2.8. Analysis of Intestinal Short-Chain Fatty Acids (SCFAs)

Mix 50 mg of fecal sample with 500 μL of methanol, 10 μL of internal standard (0.625 mg/mL 2-ethylbutyric acid), and use a handheld homogenizer for 120 s. Next, vortex for 30 s and centrifuge at 12,000 rpm for 15 min at 4 °C. Transfer 250 μL of the supernatant into a 1.5 mL centrifuge tube for concentration. Add 50 μL of methanol to the concentrate, centrifuge at 12,000 rpm for 15 min at 4 °C, and filter the supernatant through a 0.22 μm organic membrane filter to prepare for GC-MS analysis. For specifics on chromatographic and mass spectrometry conditions, please refer to the reference [22].

GC–MS was carried out on an Agilent 7890B gas chromatograph coupled to an Agilent 7000B mass spectrometer (Agilent Technologies, Santa Clara, CA, USA) using a DB-FFAP capillary column (30 m × 0.25 mm, 0.25 μm; Agilent Technologies, Santa Clara, CA, USA). Helium (≥99.999%) served as the carrier gas at 1.0 mL/min. Samples (1 μL) were injected with a 100:1 split. The oven was programmed at 40 °C for 2 min, ramped to 95 °C at 40 °C/min (1 min hold), to 140 °C at 5 °C/min, and to 200 °C at 40 °C/min, with a 240 °C post-run for 6 min. EI was used at 70 eV, with the transfer line/ion source/quadrupole set to 280/230/150 °C. Compounds were identified by full-scan acquisition (m/z 40–150) and quantified in SIM mode.

2.9. Real-Time Quantitative PCR Analysis

Homogenize 0.1 g of tissue from the ileum and isolate total RNA using the RNeasy Mini Kit (QIAGEN, Hilden, Germany)per the manufacturer’s protocol. Verify RNA integrity by electrophoresis, quantify at OD260, normalize RNA input across samples, and reverse-transcribe to cDNA. For real-time fluorescence PCR, prepare reactions in an 8-tube strip by adding 0.5 μL each of primer A and primer B, 2.0 μL of cDNA, and 20 μL of DEPC-treated water. Under light-protected conditions, add 5.0 μL of SYBR fluorescent enzyme, and include GAPDH as an internal reference in the mixture. Then, use the StepOnePlus qRT PCR™ (Applied Biosystems, Foster City, CA, USA)system to complete RT-PCR, and determine the relative gene expression levels using the 2^(−ΔΔCt) method [23].

2.10. Statistical Analysis

The data are expressed as mean ± standard deviation (mean ± SD). Statistical analysis was performed using SPSS 18.0 software, with one-way ANOVA followed by Tukey’s post hoc test for multiple comparisons; p < 0.05 was considered significant. GraphPad Prism 6 was used to plot the analysis results.

3. Results

3.1. Effects of MVP on Serum Lipid Levels in High-Fat Diet (HFD) Mice

As shown in Figure 1, we found that compared with the vehicle group, Serum TC, TG, and LDL-C levels in the model group increased significantly (57.95%, p < 0.001; 33.05%, p < 0.001; and 81.56%, p < 0.01), while HDL-C levels decreased significantly (37.61%, p < 0.05). Following MVP administration, liver TC, TG, LDL-C, and HDL-C levels significantly recovered compared with the model group. TC, TG, and LDL-C decreased by 33.44%, 27.39%, and 44.47%, respectively (p < 0.05), while HDL-C increased by 42.47% (p < 0.01; Figure 1).

3.2. Effects of MVP on Serum Oxidative-Stress Markers and Inflammatory-Cytokine Levels in HFD Mice

Compared to the vehicle group, the model group showed a significant increase in serum MDA levels (81.56%, p < 0.01) and a significant decrease in SOD levels (37.61%, p < 0.05). After administration of MVP, the MVP dose groups exhibited a significant reversal trend in SOD and MDA levels compared to the model group (42.47%, p < 0.01; 44.47%, p < 0.001; Table 1). In this experiment, compared to the vehicle group, the serum levels of IL-2, IL-6, IL-8, and TNF-α in the model group were significantly increased. Compared to the model group, the levels of IL-2, IL-6, IL-8, and TNF-α were significantly reduced (p < 0.05; Table 1).

3.3. Effects of MVP on Liver Lipid Levels and Liver Metabolic-Enzyme Levels in High-Fat Diet (HFD) Mice

Compared to the vehicle group, the model group exhibited significant increases in liver TC, TG, and LDL-C by 15.43%, 19.2%, and 16.52%, respectively (p < 0.05), along with a substantial reduction in HDL-C by 20.14% (p < 0.001). Following MVP administration, liver TC, TG, and LDL-C levels, as well as HDL-C levels, showed a significant reversal compared to the model group (p < 0.05, p < 0.001; Figure 2A). Furthermore, we observed that the activities of liver fatty acid synthase ACC and DGAT were significantly elevated in the model group compared to the vehicle group, while LPL, HL, and CPT-1 activities were significantly reduced (p < 0.05, p < 0.01; Table 2). DGAT is an indispensable enzyme in the triglyceride synthesis pathway, closely associated with lipid metabolism and deposition within the body. LPL, HL, and CPT-1, as critical enzymes for fatty acid synthesis and breakdown, showed significant changes under MVP intervention. Specifically, ACC and DGAT levels were reduced by 37.2% and 20.45% (p < 0.001), while the activities of LPL, HL, and CPT-1 increased by 25.53%, 32.3%, and 46.19%, respectively (p < 0.05; Table 2). The results indicate that MVP can significantly diminish the levels of enzymes associated with lipid production while enhancing the levels of lipid breakdown enzymes.

3.4. Histopathological Examination of Liver Tissue

H&E staining of mouse liver sections showed clear histological differences between the vehicle and model groups. In the vehicle group, the hepatic lobule structure was well-organized, and hepatocytes were uniformly arranged, indicating healthy liver conditions. In contrast, the model group exhibited notable fatty degeneration in hepatocytes, with irregularly shaped and disorganized hepatocytes, marked swelling, and the presence of numerous lipid vacuoles in the cytoplasm. Additionally, liver lobule necrosis was observed, accompanied by inflammatory cell infiltration. Crucially, compared to the model group, MVP intervention significantly reduced hepatic fatty degeneration in HFD mice, preserved the structural integrity of the hepatic lobules, alleviated hepatocyte swelling, and notably decreased inflammatory infiltration (Figure 2B).

3.5. Effects of MVP Intervention on Intestinal Barrier Function in Mice

In the model group, structural damage to the small intestinal villi was evident, including swelling, fragmentation, and shortening. Additionally, goblet cell abundance in the colon was markedly decreased, accompanied by a thinner mucus layer. After MVP supplementation, intestinal villi in the MVP group were better maintained, showing improved structural integrity and preserved length. The number of goblet cells increased, effectively mitigating intestinal mucosal damage. Furthermore, the protective effects of MVP exhibited a dose-dependent response, with the MVP-H group showing the most significant improvement (Figure 3A,B). These findings suggest that MVP attenuates intestinal barrier injury induced by a high-fat diet. RT–PCR indicated that intestinal Claudin-1, ZO-1, and Occludin mRNA levels were significantly lower in the model group than in the vehicle group (p < 0.01). MVP treatment significantly increased their transcripts (p < 0.01; Figure 3C), suggesting enhanced tight-junction gene expression. Further analysis demonstrated that these molecular-level changes were consistent with histopathological observations, where the intestinal barrier structure was impaired in the model group but showed clear signs of repair following MVP intervention. Overall, MVP alleviated high-fat diet-induced intestinal barrier impairment and largely normalized intestinal function, potentially by upregulating tight-junction proteins. GC analysis of fecal SCFAs showed lower SCFA concentrations in the model group than in the vehicle group (p < 0.05). MVP treatment significantly raised acetic, propionic, and butyric acid levels (p < 0.05; Figure 3D); in particular, acetic and propionic acid in the MVP-H group approached vehicle levels, suggesting that MVP restores key SCFAs and supports gut health.

3.6. Gut Metabolomics

3.6.1. Metabolite Identification and Analysis

Across positive- and negative-ion modes, 6764 compounds were annotated by matching to databases including KEGG and HMDB (Figure 4A). Among these, 5728 metabolites were common to the vehicle, model, and MVP groups (MVP-H groups). Upon comparison with the HMDB database, 1562 compounds were annotated to it. Furthermore, 355 compounds were annotated as lipids and lipid-like molecules, accounting for 22.73%, the highest proportion; 287 compounds were annotated as organoheterocyclic compounds, accounting for 18.37%; 269 compounds were annotated as organic acids and derivatives, representing 17.22%; 232 compounds were classified as benzenoids, making up 14.85%; 141 compounds were annotated as organic oxygen compounds, accounting for 9.03%; and 136 compounds were identified as phenylpropanoids and polyketides, constituting 8.71% (Figure 4B). Metabolite composition analysis showed that lipids, organoheterocyclic compounds, and organic acids predominated.

3.6.2. OPLS-DA

PLS-DA was performed to differentiate metabolite profiles among the normal, model, and MVP-H groups, enabling assessment of hyperlipidemia-related metabolic changes and identification of MVP-responsive biomarkers. Under both positive- and negative-ionization modes, samples clustered tightly within groups and separated clearly between groups, indicating distinct intestinal metabolic profiles across groups and supporting the validity of the hyperlipidemia model as well as the modulatory effect of MVP on intestinal metabolism (Figure 4C). Model robustness was assessed by a 200-run permutation test of the OPLS-DA model. Explanatory power (R2Y) and predictability (Q2) were evaluated, and all permuted R2/Q2 values remained below those of the original model, supporting good predictive performance with no evidence of overfitting (Figure S1). Collectively, these results support the robustness of the multivariate model and provide a reliable basis for downstream biomarker identification and efficacy evaluation.

3.6.3. Metabolic Pathway Analysis of Differentially Regulated Metabolites

After obtaining the matching information of differential metabolites, with p < 0.05 as the screening condition, the KEGG database was searched for species pathways and metabolic pathway analysis. The KEGG topological results (Figure 5A) showed significant differences in metabolic pathways between HFD and MVP intervention in mice. Specifically, the pathways significantly enriched with differential metabolites in the vehicle group versus the model group mainly included linoleic acid metabolism, arginine biosynthesis, alanine–aspartate–glutamate metabolism, arachidonic acid metabolism, pyrimidine metabolism, phosphoinositide metabolism, and phenylalanine metabolism. In contrast, the MVP group versus the model group significantly affected arachidonic acid metabolism, glutathione metabolism, alanine–aspartate–glutamate metabolism, pyrimidine metabolism, α-linolenic acid metabolism, sphingolipid metabolism, arginine biosynthesis, phenylalanine metabolism, and the pentose phosphate pathway. By enriching the top 20 metabolic pathways in both comparison groups, the intersection analysis (model group vs. vehicle group, MVP group vs. model group) revealed five common enriched pathways: arachidonic acid metabolism, alanine–aspartate–glutamate metabolism, pyrimidine metabolism, arginine biosynthesis, and phenylalanine metabolism. These results indicate that these five metabolic pathways are potential key pathways influencing lipid metabolism (Table 3).

3.6.4. Differential Metabolite Screening

Differential metabolites were screened from the OPLS-DA model using VIP > 1 together with univariate testing (p < 0.05). In total, 778 metabolites differed between the vehicle and model groups, including 363 that increased and 415 that decreased. Compared with the model group, the MVP group exhibited 334 differential metabolites, including 238 that increased and 96 that decreased (Figure 5B). In the plot, red indicates higher metabolite abundance, blue indicates lower abundance, and color intensity represents the magnitude of change. A clustered heatmap was used to visually display the changing patterns of metabolites across different groups. The top 50 metabolites ranked by VIP scores were selected as potential biomarkers, and their changes are shown in Figure 5C. Furthermore, among the top four enriched metabolic pathways in the MVP group versus the model group, two were inferred as potential key metabolic pathways. Enrichment analysis of the key differential metabolites mapped to these four pathways identified important metabolites such as arachidonic acid, 8,9-EET, glutathione, cytidine, and L-glutamate. After MVP intervention, the expression levels of these five metabolites in the hyperlipidemic mice of the MVP group showed significant reversal compared to the model group. To more intuitively display the expression differences in these five metabolites among the groups, box plots were used to compare their abundance levels across the three groups (Figure 6). Among them, two significant differential metabolites, arachidonic acid and 8,9-EET, were enriched in the arachidonic acid metabolic pathway; glutathione was distributed in the glutathione metabolic pathway; cytidine belonged to the pyrimidine metabolic pathway; additionally, L-glutamate was enriched in both the alanine–aspartate–glutamate metabolism and glutathione metabolic pathways (Figure 7A). Relative to the vehicle group, the model group showed higher levels of arachidonic acid, whereas 8,9-EET, glutathione, cytidine and L-glutamate were reduced. The results suggest that MVP may improve the hyperlipidemic state in mice by regulating the expression of these key metabolic pathways and related differential metabolites.

3.6.5. Association Analysis of Key Intestinal Metabolites with Biochemical Parameters

Following the assessment of serum inflammatory markers, hepatic biochemical indices, and differential intestinal metabolites in HFD-induced obese mice treated with MVP, correlations were examined using Spearman’s rank correlation analysis (Figure 7B). The results showed that several metabolites were significantly associated with the measured biochemical parameters. Specifically, HL showed a positive correlation with L-glutamate but negative correlations with dimethyl trisulfide, calcitriol, and p-fluorophenylalanine, as well as significant negative correlations with kyotorphin and cytidine. LDL-C showed a positive association with arachidonate, whereas it was inversely associated with L-glutamic acid and ethyl icosapentate; it also displayed significant negative correlations with 4-hydroxycinnamic acid and dimethyl trisulfide. Additionally, protriptyline was found to have a significant positive correlation only with TC. Metabolites positively correlated with IL-10 included p-fluorophenylalanine, kyotorphin, and cytidine, while a significant positive correlation was observed with 13(S)-HPOT. IL-6 showed positive correlations only with kyotorphin, cytidine, and myo-inositol and no correlations with other metabolites. HDL-C was negatively correlated with myo-inositol.

4. Discussion

Lipid metabolism disorder is a pathological state triggered by excessive fat accumulation in the body. Studies have shown that long-term consumption of a high-fat diet significantly increases body weight and fat deposition, accompanied by abnormal changes in blood lipid indicators [24]. TC and TG are primarily synthesized in the liver. Prolonged HFD disrupts lipid metabolism balance, leading to elevated serum levels of TG, TC, and LDL-C, as well as reduced HDL, which are the main causes of hyperlipidemia. Therefore, serum levels of TG, TC, LDL-C, and HDL-C reflect the severity of hyperlipidemia. Additionally, low HDL-C levels contribute to a higher incidence of cardiovascular diseases, while high HDL-C levels help combat atherosclerosis and inhibit ox-LDL, protecting endothelial cells from the cytotoxic effects of ox-LDL [25,26]. This study’s serum biochemical analysis data on MVP intervention in hyperlipidemic mice align with findings from research on Lycium barbarum polysaccharides, mushroom polysaccharides, and previous studies on the combined effects of sea buckthorn polysaccharides and astragalus polysaccharides. Specifically, they markedly ameliorate HFD-induced metabolic disturbances by lowering TG, TC and LDL-C and concomitantly elevating HDL-C [27,28,29]. In addition, the further harm of lipid metabolism disorders is often manifested through the amplification of inflammation. The onset of atherosclerosis begins with hyperlipidemia, which promotes the accumulation of ox-LDL within the vascular wall, directly impairing endothelial cell function and initiating the pathological process. In this core mechanism, ox-LDL continuously drives a series of inflammatory reactions, promoting the expression and release of various inflammatory cytokines (e.g., IL-1β, IL-6, TNF-α), exacerbating local vascular inflammation [30]. Ultimately, this results in the liver synthesizing CRP, a crucial serum biomarker for monitoring inflammatory activity in atherosclerosis in clinical practice [31]. Experimental data indicate that MVP can effectively reduce the expression of inflammatory factors, suggesting that MVP may improve inflammation in HFD-induced mice by alleviating inflammatory responses.

The liver is the central organ for lipid metabolism and plays a crucial role in maintaining systemic lipid homeostasis. Under prolonged hyperlipidemic conditions, excessive lipid accumulation in hepatocytes leads to the disruption of cell membrane structures, thereby inducing liver injury [32]. MDA is a key lipid peroxidation product that can interact with membrane proteins and enzymes, compromising membrane integrity, disturbing cellular function, and promoting tissue injury [33]. SOD is a widely distributed metalloenzyme that removes free radicals and helps protect lipids from oxidative damage [34]. This study is consistent with reports on jujube vinegar and, separately, Liubao tea extract, indicating that increasing SOD and GSH-Px activity can alleviate oxidative damage associated with hyperlipidemia [35,36]. HL hydrolyzes triglycerides and phospholipids in circulating lipoproteins, participates in the remodeling of LDL/HDL by regulating lipoprotein composition and particle size, thereby accelerating the metabolism and clearance of lipoprotein remnants in the liver [37]. CPT-1 catalyzes the rate-limiting step that enables long-chain fatty acids to enter mitochondria for β-oxidation. Increased CPT-1 activity reflects stronger fatty acid β-oxidation in hepatocytes, promoting lipid clearance and reducing lipid peroxidation products (e.g., MDA), which in turn helps limit mitochondria damage driven by membrane lipid peroxidation [38,39]. In this study, MVP significantly ameliorated hyperlipidemia-induced liver injury through a dual mechanism of synergistic antioxidant effects and activation of lipolytic enzymes (HL, CPT-1). Pathological staining showed that the MVP-H group had markedly less hepatocyte ballooning, with tissue architecture closer to the vehicle group and clearly improved compared with the model group. In conclusion, this experiment demonstrates that MVP-H has significant lipid-lowering effects and improves liver tissue pathology in hyperlipidemic mice.

Metabolomics mainly involves the analysis of metabolite profiles and metabolic pathways, which can clarify the relationships between relevant metabolites and physiological and biochemical markers, dynamically monitor physiological and pathological processes, and provide new tools for exploring disease-related biomarkers and pathogenesis. Therefore, this study employed untargeted metabolomics to investigate the mechanisms and effects of MVP on the metabolites and metabolic pathways in the intestinal tissues of HFD mice.

Metabolomic analysis revealed that both HFD and MVP treatment significantly influenced several core metabolic pathways, including arachidonic acid, glutathione, alanine–aspartate–glutamate, and pyrimidine metabolism. To investigate the potential mechanisms by which MVP modulates lipid metabolism, we further analyzed key metabolites in the top four enriched metabolic pathways between the MVP group and the model group. This analysis identified major metabolites associated with lipid metabolism and inflammation, including arachidonic acid, 8,9-EET, glutathione, cytidine, and L-glutamic acid. Among these, arachidonic acid metabolism was the most significant pathway. Arachidonic acid is a polyunsaturated fatty acid that is esterified in membrane phospholipids [40]. When released from membrane phospholipids upon stimulation, arachidonic acid is primarily metabolized via COX (prostaglandin G/H synthase), LOX (heme-free dioxygenase), and CYP450 pathways, generating various oxylipins such as prostaglandins, leukotrienes, and epoxyeicosatrienoic acids (EETs). These lipid mediators collectively participate in lipid accumulation and inflammatory amplification [41,42,43]. Moreover, arachidonic acid promotes fatty acid oxidation by participating in oxidative lipid metabolism, thereby enhancing the efficiency of fatty acid-derived energy utilization [44]. 8,9-EET is an isomer of EETs, CYP450-derived metabolites implicated as promising targets for cardiovascular therapy, largely because they promote vasodilation, suppress inflammation, and support mitochondrial function [45]. Additionally, by activating the PPARα receptor, EETs can alleviate cardiac hypertrophy and fibrosis, inhibit NF-κB-mediated inflammatory responses, and reduce the expression of inflammatory factors [46]. In addition, EETs have been reported to confer protective effects in inflammation-related diseases, including atherosclerosis and diabetic complications [47]. The experiment revealed that the model group exhibited significantly lower levels of arachidonic acid and 8,9-EET compared with the control group, potentially indicating that the high-fat diet altered the lipid-derived mediator pool and disturbed fatty acid metabolism. In contrast, the MVP-H group showed a notable increase in the levels of these two metabolites compared to the model group, suggesting its potential role in modulating lipid mediator homeostasis. This provides a scientific basis for the lipid-lowering effect of MVP. Studies have shown that in non-alcoholic fatty liver disease, glutathione deficiency exacerbates mitochondrial damage and cholesterol crystal formation, thereby triggering an inflammatory response. Conversely, elevated GSH levels strengthen antioxidant defenses and help reduce oxidative-stress-related liver injury [48]. Recent evidence indicates that glycine derivatives promote de novo GSH synthesis, upregulating fatty acid oxidation genes (e.g., ACAA2, CPT1A) and ameliorating HFD-induced steatosis [49]. In this study, HFD induced a significant depletion of intestinal GSH, which was effectively reversed by MVP intervention. The expression level of GSH may regulate dyslipidemia by modulating the intestinal redox buffering capacity. L-glutamate is a pivotal node in the alanine–aspartate–glutamate network and supplies substrate for GSH biosynthesis. Via transamination to α-ketoglutarate, it links amino acid metabolism to mitochondrial energy production. In the gut, intestinal epithelial cells oxidize glutamate as a key fuel, supporting mucosal redox balance and tight-junction integrity. Improved barrier function can consequently limit the portal influx of inflammatory stimuli to the liver, thereby attenuating hepatic inflammation and lowering the risk of metabolic dysregulation [50,51]. The Yinlan Lipid-Lowering Capsule reversed hyperlipidemia in mice by upregulating metabolites such as L-glutamate [52], consistent with the findings of this study. Thus, L-glutamate may represent a key metabolite in the MVP group that is associated with lipid metabolism regulation in HFD-fed mice. Beyond redox-related metabolites, we also observed modulation of pyrimidine metabolism. Cytidine is an intermediate product of pyrimidine metabolism and can be enzymatically converted into uridine [53]. Uridine has been reported to improve lipid accumulation by modulating gut microbiota composition [54,55]. Cytidine alleviates dyslipidemia by increasing the abundance of gut microbiota that produce short-chain fatty acids in ob/ob mice [56]. This study found that MVP intervention significantly reversed the expression levels of cytidine in the MVP group compared to the model group, suggesting that cytidine may participate in lipid metabolism regulation in HFD mice by modulating gut microbiota abundance. The MVP-induced reversal of cytidine levels indicates a potential role for gut microbiome-mediated regulation in its lipid-lowering effects. However, microbiota-mediated mechanisms should be validated using integrated microbiome profiling and quantitative SCFA and bile acid profiling. In conclusion, MVP ameliorates HFD-induced hyperlipidemia through a multitargeted mechanism, coordinately regulating a network of critical metabolic pathways and key effector metabolites. These findings provide a foundational framework for further investigation into the therapeutic application of MVP for metabolic syndrome. Finally, all findings are based on a mouse model of hyperlipidemia induced by a high-fat diet, which may not fully replicate the complex pathophysiological features of human metabolic syndrome. Follow-up studies should combine targeted metabolite quantification with further microbiome analysis.

5. Conclusions

In summary, this study demonstrates that MVP reduces serum lipid levels and improves liver pathological indicators in mice with high-fat-diet-induced hyperlipidaemia. Gut metabolomics showed consistent shifts in metabolic profiles. The main changes mapped to arachidonic acid metabolism, glutathione metabolism, alanine–aspartate–glutamate metabolism and pyrimidine metabolism. Together, these results underscore the value of gut metabolomics for mechanistic insight and support an in vivo lipid-lowering effect of MVP. However, the current evidence primarily links MVP intervention to pathway-level metabolic alterations and does not establish causal targets. Overall, MVP shows promise as a functional food ingredient for regulating lipid metabolism. Future work should integrate multi-omics approaches, including combined gut microbiota and transcriptomics, to validate and refine the underlying mechanisms and key effectors.